【摘要】 随着生成式AI技术在教育领域的深度渗透，职前教师在技术适应过程中的情绪动态与策略选择对教学质量的影响日益凸显。本研究基于压力交互理论，通过对11名职前教师的深度访谈与主题编码分析，系统探究其在生成式AI教学应用中的情绪体验及应对策略。研究发现，职前教师的情绪体验呈现多维度特征，并与技术交互质量密切相关：积极情绪主要体现为技术赋能带来的惊喜、效率提升引发的愉悦等，而消极情绪则多源于技术低效导致的烦躁、数据不可靠引发的质疑等。在应对策略方面，教师表现出动态多元的反应模式，可分为趋近型（如积极重评、人机协同等）与回避型（如技术疏离、心理妥协等）两类策略。本研究揭示了情绪与应对在生成式AI教学情境中的联动机制与适应路径，深化了对“技术工具性”与“教师主体性”之间张力的理解，并为构建有效的人机协同教学边界提供了理论支撑与实证依据。更多还原

【Abstract】 With the deepening integration of Generative Artificial Intelligence(GenAI) in education, pre-service teachers’ emotional dynamics and coping choices during technology adaptation have become increasingly consequential for teaching quality. Drawing on Lazarus and Folkman’s transactional theory of stress and coping, this study investigated pre-service teachers’ emotional experiences and coping strategies in GenAI-assisted teaching. Data were collected through in-depth interviews with 11 pre-service teachers and analyzed using thematic coding. The findings indicate that participants’ emotional experiences are multidimensional and closely tied to the quality of human-AI interaction. Positive emotions primarily stem from feelings of empowerment(e. g., surprise at GenAI-enabled possibilities) and enjoyment triggered by enhanced efficiency, whereas negative emotions are largely associated with ineffective system performance(e. g., irritation) and concerns about unreliable outputs(e.g., skepticism). In terms of coping, teachers demonstrated dynamic and diverse response patterns that can be categorized into two broad types: approach-oriented coping(e. g., positive reappraisal, human-AI collaboration) and avoidanceoriented coping(e. g., distancing from technology, psychological compromise). This study elucidates the linkage mechanisms and adaptive pathways between emotions and coping in GenAIassisted teaching, deepens understanding of the tension between technological instrumentality and teacher agency, and offers theoretical and empirical implications for delineating effective boundaries of human-AI collaborative teaching.更多还原